arXiv:2305.03025
공식 코드 · Papers with Code
Panda LLM: Training Data and Evaluation for Open-Sourced Chinese Instruction-Following Large Language Models
원문 초록
This project focuses on enhancing open-source large language models through instruction-tuning and providing comprehensive evaluations of their performance. We explore how various training data factors, such as quantity, quality, and linguistic distribution, influence the performance of instruction-tuned models trained on publicly accessible high-quality instruction datasets for both English and Chinese languages. Our goal is to supplement evaluation with quantitative analyses, providing valuable insights for the continued advancement of open-source chat models. Our model, data, and code are publicly available for others to use and build upon.
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LLaVA-Pose: Enhancing Human Pose and Action Understanding via Keypoint-Integrated Instruction Tuning
InstructTTSEval: Benchmarking Complex Natural-Language Instruction Following in Text-to-Speech Systems
토론
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